The Use of Data Mining to Identify Primary Teacher Qualification Demand in Indonesia

The use of big data for knowledge retrieval has been a significant trend in recent years, transforming how information is accessed and utilized. Data mining plays a crucial role in supporting research trends in big data by enabling the extraction of valuable patterns, insights, and knowledge from large and complex datasets. One of the potentials of big data that can be optimized is job vacancy data which can provide direction for the development of a profession. One of the professions with rapidly developing needs along with the development of society is the teacher profession. Job vacancy data with large volume, variety, and velocity can be a source of knowledge that can provide direction for knowledge development and research to support the development of the teacher profession, especially in Indonesia. There is not much research that analyzes teacher-related job vacancy data into knowledge with valuable patterns, insights, and knowledge. This research aims to provide knowledge by data mining on teacher qualifications needed in schools and educational institutions in Indonesia. This research uses a digital humanities approach by implementing data mining to optimize job vacancy information big data of elementary schools and educational institutions in Indonesia, in the job search portals. This research proposed knowledge containing information from 215 schools and educational institutions that classified teacher qualification needs in terms of pedagogical, professional, social, and personality competency aspects. The results of this research can serve as an input for education stakeholders in higher education institutions, researchers, and individual teacher candidates in preparing quality teachers for the sake of equalizing the quality of education in Indonesia.